Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT

Tsu Chi Cheng, Nan Tsing Chiu, Yu Hua Fang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.

Original languageEnglish
Title of host publicationFuture Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019
EditorsKang-Ping Lin, Ratko Magjarevic, Paulo de Carvalho
PublisherSpringer
Pages138-142
Number of pages5
ISBN (Print)9783030306359
DOIs
Publication statusPublished - 2020 Jan 1
Event4th International Conference on Biomedical and Health Informatics, ICBHI 2019 - Taipei, Taiwan
Duration: 2019 Apr 172019 Apr 20

Publication series

NameIFMBE Proceedings
Volume74
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277

Conference

Conference4th International Conference on Biomedical and Health Informatics, ICBHI 2019
CountryTaiwan
CityTaipei
Period19-04-1719-04-20

Fingerprint

Positron emission tomography
Tomography
Glucose
Cells
Computer aided diagnosis
Drainage

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Biomedical Engineering

Cite this

Cheng, T. C., Chiu, N. T., & Fang, Y. H. (2020). Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. In K-P. Lin, R. Magjarevic, & P. de Carvalho (Eds.), Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019 (pp. 138-142). (IFMBE Proceedings; Vol. 74). Springer. https://doi.org/10.1007/978-3-030-30636-6_20
Cheng, Tsu Chi ; Chiu, Nan Tsing ; Fang, Yu Hua. / Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019. editor / Kang-Ping Lin ; Ratko Magjarevic ; Paulo de Carvalho. Springer, 2020. pp. 138-142 (IFMBE Proceedings).
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title = "Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT",
abstract = "Lung Cancer is a leading cause of death worldwide, and about 85{\%} of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85{\%}, a sensitivity of 82{\%} and a specificity of 85{\%}.",
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Cheng, TC, Chiu, NT & Fang, YH 2020, Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. in K-P Lin, R Magjarevic & P de Carvalho (eds), Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019. IFMBE Proceedings, vol. 74, Springer, pp. 138-142, 4th International Conference on Biomedical and Health Informatics, ICBHI 2019, Taipei, Taiwan, 19-04-17. https://doi.org/10.1007/978-3-030-30636-6_20

Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. / Cheng, Tsu Chi; Chiu, Nan Tsing; Fang, Yu Hua.

Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019. ed. / Kang-Ping Lin; Ratko Magjarevic; Paulo de Carvalho. Springer, 2020. p. 138-142 (IFMBE Proceedings; Vol. 74).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.

AB - Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.

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Cheng TC, Chiu NT, Fang YH. Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT. In Lin K-P, Magjarevic R, de Carvalho P, editors, Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019. Springer. 2020. p. 138-142. (IFMBE Proceedings). https://doi.org/10.1007/978-3-030-30636-6_20